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Lead Data Scientist

at Railinc

Posted: 5/3/2019
Job Status: Full Time
Job Reference #: 0bf87568-7bb1-4013-97e8-cc3e72cf8194

Job Description

Lead Data Scientist - Position Description                                                                           

Primary Accountability/Responsibility:  Responsible for modeling complex business problems, discovering business insights and identifying opportunities through the use of statistical, algorithmic, data mining, machine learning, and visualization techniques. In addition to advanced data analytics skills, this role is also proficient at integrating and preparing large, varied datasets, and communicating results and recommendations based on the model/analysis to both technical and non-technical audiences. This role is also able to recommend the most effective data science approaches for various challenges and will be able to implement these approaches independently without guidance as well as guide other data scientists in their efforts. Additionally, the lead data scientist will be able to manage data science teams and help drive the organization’s technology vision, be up to date with the state of technology, and help ensure the organization makes forward-looking strategic decisions in its data science approach.

Job Accountability


Key Measures

Essential Functions

·    35%: Conduct analytical research, develop prototypes and contribute to production-ready solutions.  Business domains include but are not limited to:

o   Fleet Utilization for Railroads and Equipment Owners

o   Miles & time between car repair incidents

o   Railroad yard traffic predictions

o   Predictive modeling of maintenance, ETAs, etc.

o   Internal measurement development

o   Data quality evaluations

o   Data enrichment

o   Prototype reports to be included in production systems

·    35%: Deliver analytical projects by:

o   Working with project managers to define schedule and deliver results to all customers and internal stakeholders and managing expectations

o   Collaborating with IT resources to develop and optimize production solutions

o   Creating and documenting repeatable solutions for meeting ongoing customer needs

o   Communicating the results and methodology to internal and external stakeholders

·    20%: Drive the organization’s data science and technology vision through research on the state of the art in data science technologies to ensure forward-thinking strategic decisions and recommendations


·    10%: Gather, interpret, and translate customer needs into business problems that can be solved via advanced analytics methodologies by:

o   Working with business stakeholders and/or facilitate data analysis opportunity discussions

o   Leading solution analysis, definition, and requirements gathering for data services

o   Prioritizing data analysis using rail industry priorities & business cases

·    Collaborate with other data scientists to drive data analysis methodology, repeatable and structured

·    Exercise judgment within generally defined practices and policies in selecting methods and techniques for obtaining solutions

·    Takes the lead on analytical projects, and may lead the projects of other data scientists and analytical consultants

·    Work with manager to finalize priority and deadlines, and adjust & communicate as necessary

·    Customer feedback and delivery against commitments

Non-Essential Functions

·    Support and improve internal decision making

·    Develop measurement dashboards

·    Conduct and report industry trend and market analysis to meet industry needs

·    Performs other duties as assigned

·    Customer feedback and delivery against commitments

Success Factors:

·    Knowledge/Skills/Abilities

Minimum Requirements

·         Superior analytical skills with working knowledge of basic statistical, predictive and optimization models

·         Experience in leading and managing data science teams

·         Strong programming proficiency and working experience (10 years) in a subset of Python, R, Scala, Java (Python preferred)

·         Strong proficiency and experience (10 years) with data science and machine learning software stacks, e.g. NumPy, Pandas, SK-learn for Python

·         Programming proficiency in Spark and MLlib (3 years)

·         Working experience with and understanding of large-scale data analysis systems, e.g. Hadoop or MPP databases (5 years)

·         Proficiency and experience with SQL (10 years)

·         Significant experience (10 years) implementing machine learning and data science models, including through production

·         Strong theoretical and practical knowledge of machine learning models and algorithms (unsupervised and supervised), their use in applications, and their advantages and disadvantages

·         Strong knowledge of code-based data visualization tools (e.g. matplotlib) for data exploration and to present models and results to internal and external stakeholders

·         Experience with cloud-based systems and toolsets (3 years)

·         Experience and understanding of experiment design and evaluation

·         Knowledge of big data engineering toolsets a plus

·         Superior data preparation skills; be able to access, transform and manipulate Railinc and external customer data in its base form

·         Superior problem-solving skills

·         Entrepreneurial mindset and business understanding

·         Up to date with the state of the art in the data science technology and related infrastructure and services space

·         Strong team management and leadership skills

·         Strong verbal and written communication skills

·         Ability to work effectively with clients, IT management, business management, project managers, and IT staff

·         Ability to manage multiple activities in a deadline-oriented environment; highly organized and flexible

·         Ability to work independently and jointly in unstructured environments in a self-directed way

·         Ability to take a leadership role on engagements and with customers

·         Strong teamwork skills and ability to work effectively with multiple internal customers

Additional Requirements:

·    Education

·    Experience

·    Certifications

·    Advanced degree (PhD or Masters) in an analytical or technical field (e.g. applied mathematics, statistics, physics, computer science, operations research, business, economics)

·    A minimum of 10 years related work experience

·    Strong statistical analysis and methodology experience

·    Experience with analytics tools and big data platforms

·    Experience with business intelligence and analytics

Physical Requirements


List physical activities and requirements, including but not limited to:


·         Sedentary work:  assignment involves sitting at workstation (desk) most of the time (up to 8 hours) with only occasional walking and/or standing

·         Keyboarding:  Primarily using fingers for typing

·         Talking:  Expressing or communicating verbally through use of spoken words (accurately conveying detailed or important spoken instructions to others)

·         Hearing:  Ability to receive detailed information through oral communication and to make discriminations in sound.

·         Visual:  Through close visual acuity, required to perform activities such as:  preparing and analyzing data and figures; transcribing; viewing computer terminal; extensive reading (with or without correction)

·         Environment:  work is performed within an office setting and therefore no substantial exposure to adverse environmental conditions (i.e. extreme heat, cold, noise, etc.).  Customer visits may be done at railroad facilities, which would require appropriate safety equipment.

·         Travel:  Some travel may be required (up to 25%).